penaltyLearning: Penalty Learning

Implementations of algorithms from Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression, by Hocking, Rigaill, Vert, Bach <http://proceedings.mlr.press/v28/hocking13.html> published in proceedings of ICML2013.

Version: 2024.9.3
Depends: R (≥ 2.10)
Imports: data.table (≥ 1.9.8), ggplot2
Suggests: neuroblastoma, jointseg, testthat, future, future.apply, directlabels (≥ 2017.03.31)
Published: 2024-10-02
DOI: 10.32614/CRAN.package.penaltyLearning
Author: Toby Dylan Hocking [aut, cre]
Maintainer: Toby Dylan Hocking <toby.hocking at r-project.org>
BugReports: https://github.com/tdhock/penaltyLearning/issues
License: GPL-3
URL: https://github.com/tdhock/penaltyLearning
NeedsCompilation: yes
Materials: NEWS
CRAN checks: penaltyLearning results

Documentation:

Reference manual: penaltyLearning.pdf

Downloads:

Package source: penaltyLearning_2024.9.3.tar.gz
Windows binaries: r-devel: penaltyLearning_2024.9.3.zip, r-release: penaltyLearning_2024.9.3.zip, r-oldrel: penaltyLearning_2024.9.3.zip
macOS binaries: r-release (arm64): penaltyLearning_2024.9.3.tgz, r-oldrel (arm64): penaltyLearning_2024.9.3.tgz, r-release (x86_64): penaltyLearning_2024.9.3.tgz, r-oldrel (x86_64): penaltyLearning_2024.9.3.tgz
Old sources: penaltyLearning archive

Reverse dependencies:

Reverse imports: PeakSegJoint, PeakSegOptimal
Reverse suggests: aum, binsegRcpp, PeakSegDP

Linking:

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